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Prediction of standard enthalpy of combustion of pure compounds using a very accurate group-contribution-based method

Gharagheizi, F ; Sharif University of Technology | 2011

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  1. Type of Document: Article
  2. DOI: 10.1021/ef200081a
  3. Publisher: 2011
  4. Abstract:
  5. The artificial neural network-group contribution (ANN-GC) method is applied to estimate the standard enthalpy of combustion of pure chemical compounds. A total of 4590 pure compounds from various chemical families are investigated to propose a comprehensive and predictive model. The obtained results show the squared correlation coefficient (R 2) of 0.999 99, root mean square error of 12.57 kJ/mol, and average absolute deviation lower than 0.16% for the estimated properties from existing experimental values
  6. Keywords:
  7. Average absolute deviation ; Chemical family ; Experimental values ; Predictive models ; Pure compounds ; Root mean square errors ; Squared correlation coefficients ; Standard enthalpy ; Combustion ; Enthalpy ; Neural networks ; Chemical compounds
  8. Source: Energy and Fuels ; Volume 25, Issue 6 , April , 2011 , Pages 2651-2654 ; 08870624 (ISSN)
  9. URL: http://pubs.acs.org/doi/abs/10.1021/ef200081a